Electromagnetic Brain Imaging
A Bayesian Perspective
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Beschreibung
This graduate level textbook provides a coherent introduction to the body of main-stream algorithms used in electromagnetic brain imaging, with specific emphasis on novel Bayesian algorithms. It helps readers to more easily understand literature in biomedical engineering and related fields, and be ready to pursue research in either the engineering or the neuroscientific aspects of electromagnetic brain imaging. This textbook will not only appeal to graduate students but all scientists and engineers engaged in research on electromagnetic brain imaging.
This graduate level textbook provides a coherent introduction to the body of main-stream algorithms used in electromagnetic brain imaging, with specific emphasis on novel Bayesian algorithms. It helps readers to more easily understand literature in biomedical engineering and related fields and be ready to pursue research in either the engineering or the neuroscientific aspects of electromagnetic brain imaging. This textbook will not only appeal to graduate students but all scientists and engineers engaged in research on electromagnetic brain imaging.
Provides a theoretical framework for source imaging methodology Specific focus on Bayesian algorithms Unique approach to the recent advances Includes supplementary material: sn.pub/extras
Autor*in
Kensuke Sekihara
Themen in »Electromagnetic Brain Imaging«
Bayesian algorithms Brain source reconstruction methods using MEG and EEG Electromagnetic brain imaging MEG / EEG Noninvasive reconstructions of brain activity and connectivity Signal processing algorithms